Evidence for the Accretion of Gas in Star-forming Galaxies: High N/O Abundances in Regions of Anomalously Low Metallicity

While all models for the evolution of galaxies require the accretion of gas to sustain their growth via on-going star formation, it has proven difficult to directly detect this inflowing material. In this paper we use data of nearby star-forming galaxies in the SDSS IV Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey to search for evidence of accretion imprinted in the chemical composition of the interstellar medium. We measure both the O/H and N/O abundance ratios in regions previously identified as having anomalously low values of O/H. We show that the unusual locations of these regions in the N/O vs. O/H plane indicate that they have been created through the mixing of disk gas having higher metallicity with accreted gas having lower metallicity. Taken together with previous analysis on these anomalously low-metallicity regions, these results imply that accretion of metal-poor gas can probably sustain star formation in present-day late-type galaxies.ERC STF

Virtual player design using self-learning via competitive coevolutionary algorithms

The Google Artificial Intelligence (AI) Challenge is an international contest the objective of which is to program the AI in a two-player real time strategy (RTS) game. This AI is an autonomous computer program that governs the actions that one of the two players executes during the game according to the state of play. The entries are evaluated via a competition mechanism consisting of two-player rounds where each entry is tested against others. This paper describes the use of competitive coevolutionary (CC) algorithms for the automatic generation of winning game strategies in Planet Wars, the RTS game associated with the 2010 contest. Three different versions of a prime algorithm have been tested. Their common nexus is not only the use of a Hall-of-Fame (HoF) to keep note of the winners of past coevolutions but also the employment of an archive of experienced players, termed the hall-of-celebrities (HoC), that puts pressure on the optimization process and guides the search to increase the strength of the solutions; their differences come from the periodical updating of the HoF on the basis of quality and diversity metrics. The goal is to optimize the AI by means of a self-learning process guided by coevolutionary search and competitive evaluation. An empirical study on the performance of a number of variants of the proposed algorithms is described and a statistical analysis of the results is conducted. In addition to the attainment of competitive bots we also conclude that the incorporation of the HoC inside the primary algorithm helps to reduce the effects of cycling caused by the use of HoF in CC algorithms.This work is partially supported by Spanish MICINN under Project ANYSELF (TIN2011-28627-C04-01),3 by Junta de Andalucía under Project P10-TIC-6083 (DNEMESIS) and by Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech

The systemic lupus erythematosus IRF5 risk haplotype is associated with systemic sclerosis

Systemic sclerosis (SSc) is a fibrotic autoimmune disease in which the genetic component plays an important role. One of the strongest SSc association signals outside the human leukocyte antigen (HLA) region corresponds to interferon (IFN) regulatory factor 5 (IRF5), a major regulator of the type I IFN pathway. In this study we aimed to evaluate whether three different haplotypic blocks within this locus, which have been shown to alter the protein function influencing systemic lupus erythematosus (SLE) susceptibility, are involved in SSc susceptibility and clinical phenotypes. For that purpose, we genotyped one representative single-nucleotide polymorphism (SNP) of each block (rs10488631, rs2004640, and rs4728142) in a total of 3,361 SSc patients and 4,012 unaffected controls of Caucasian origin from Spain, Germany, The Netherlands, Italy and United Kingdom. A meta-analysis of the allele frequencies was performed to analyse the overall effect of these IRF5 genetic variants on SSc. Allelic combination and dependency tests were also carried out. The three SNPs showed strong associations with the global disease (rs4728142: P = 1.34×10<sup>−8</sup>, OR = 1.22, CI 95% = 1.14–1.30; rs2004640: P = 4.60×10<sup>−7</sup>, OR = 0.84, CI 95% = 0.78–0.90; rs10488631: P = 7.53×10<sup>−20</sup>, OR = 1.63, CI 95% = 1.47–1.81). However, the association of rs2004640 with SSc was not independent of rs4728142 (conditioned P = 0.598). The haplotype containing the risk alleles (rs4728142*A-rs2004640*T-rs10488631*C: P = 9.04×10<sup>−22</sup>, OR = 1.75, CI 95% = 1.56–1.97) better explained the observed association (likelihood P-value = 1.48×10<sup>−4</sup>), suggesting an additive effect of the three haplotypic blocks. No statistical significance was observed in the comparisons amongst SSc patients with and without the main clinical characteristics. Our data clearly indicate that the SLE risk haplotype also influences SSc predisposition, and that this association is not sub-phenotype-specific

Non-L\'evy mobility patterns of Mexican Me'Phaa peasants searching for fuelwood

We measured mobility patterns that describe walking trajectories of individual Me'Phaa peasants searching and collecting fuelwood in the forests of "La Monta\~na de Guerrero" in Mexico. These one-day excursions typically follow a mixed pattern of nearly-constant steps when individuals displace from their homes towards potential collecting sites and a mixed pattern of steps of different lengths when actually searching for fallen wood in the forest. Displacements in the searching phase seem not to be compatible with L\'evy flights described by power-laws with optimal scaling exponents. These findings however can be interpreted in the light of deterministic searching on heavily degraded landscapes where the interaction of the individuals with their scarce environment produces alternative searching strategies than the expected L\'evy flights. These results have important implications for future management and restoration of degraded forests and the improvement of the ecological services they may provide to their inhabitants.Comment: 15 pages, 4 figures. First version submitted to Human Ecology. The final publication will be available at http://www.springerlink.co

Dual effects of phytoestrogens result in u-shaped dose-response curves.

Endocrine disruptors can affect the endocrine system without directly interacting with receptors, for example, by interfering with the synthesis or metabolism of steroid hormones. The aromatase that converts testosterone to 17beta-estradiol is a possible target. In this paper we describe an assay that simultaneously detects aromatase inhibition and estrogenicity. The principle is similar to that of other MCF-7 estrogenicity assays, but with a fixed amount of testosterone added. The endogenous aromatase activity in MCF-7 cells converts some of the testosterone to 17beta-estradiol, which is assayed by quantifying differences in the expression level of the estrogen-induced pS2 mRNA. Potential aromatase inhibitors can be identified by a dose-dependent reduction in the pS2 mRNA expression level after exposure to testosterone and the test compound. Using this assay, we have investigated several compounds, including synthetic chemicals and phytoestrogens, for aromatase inhibition. The phytoestrogens, except genistein, were aromatase inhibitors at low concentrations (< 1 micro M) but estrogenic at higher concentrations (greater than or equal to 1 micro M), resulting in U-shaped dose-response curves. None of the tested synthetic chemicals were aromatase inhibitors. The low-dose aromatase inhibition distinguished phytoestrogens from other estrogenic compounds and may partly explain reports about antiestrogenic properties of phytoestrogens. Aromatase inhibition may play an important role in the protective effects of phytoestrogens against breast cancer

Towards a Taxonomy of Cognitive RPA Components

Robotic Process Automation (RPA) is a discipline that is increasingly growing hand in hand with Artificial Intelligence (AI) and Machine Learning enabling the so-called cognitive automation. In such context, the existing RPA platforms that include AI-based solutions clas sify their components, i.e. constituting part of a robot that performs a set of actions, in a way that seems to obey market or business deci sions instead of common-sense rules. To be more precise, components that present similar functionality are identified with different names and grouped in different ways depending on the platform that provides the components. Therefore, the analysis of different cognitive RPA platforms to check their suitability for facing a specific need is typically a time consuming and error-prone task. To overcome this problem and to pro vide users with support in the development of an RPA project, this paper proposes a method for the systematic construction of a taxonomy of cognitive RPA components. Moreover, such a method is applied over components that solve selected real-world use cases from the industry obtaining promising resultsMinisterio de Economía y Competitividad TIN2016-76956-C3-2-RJunta de Andalucía CEI-12-TIC021Centro para el Desarrollo Tecnológico Industrial P011-19/E0

Nut production in Bertholletia excelsa across a logged forest mosaic: implications for multiple forest use

Although many examples of multiple-use forest management may be found in tropical smallholder systems, few studies provide empirical support for the integration of selective timber harvesting with non-timber forest product (NTFP) extraction. Brazil nut (Bertholletia excelsa, Lecythidaceae) is one of the world’s most economically-important NTFP species extracted almost entirely from natural forests across the Amazon Basin. An obligate out-crosser, Brazil nut flowers are pollinated by large-bodied bees, a process resulting in a hard round fruit that takes up to 14 months to mature. As many smallholders turn to the financial security provided by timber, Brazil nut fruits are increasingly being harvested in logged forests. We tested the influence of tree and stand-level covariates (distance to nearest cut stump and local logging intensity) on total nut production at the individual tree level in five recently logged Brazil nut concessions covering about 4000 ha of forest in Madre de Dios, Peru. Our field team accompanied Brazil nut harvesters during the traditional harvest period (January-April 2012 and January-April 2013) in order to collect data on fruit production. Three hundred and ninety-nine (approximately 80%) of the 499 trees included in this study were at least 100 m from the nearest cut stump, suggesting that concessionaires avoid logging near adult Brazil nut trees. Yet even for those trees on the edge of logging gaps, distance to nearest cut stump and local logging intensity did not have a statistically significant influence on Brazil nut production at the applied logging intensities (typically 1–2 timber trees removed per ha). In one concession where at least 4 trees ha-1 were removed, however, the logging intensity covariate resulted in a marginally significant (0.09) P value, highlighting a potential risk for a drop in nut production at higher intensities. While we do not suggest that logging activities should be completely avoided in Brazil nut rich forests, when a buffer zone cannot be observed, low logging intensities should be implemented. The sustainability of this integrated management system will ultimately depend on a complex series of socioeconomic and ecological interactions. Yet we submit that our study provides an important initial step in understanding the compatibility of timber harvesting with a high value NTFP, potentially allowing for diversification of forest use strategies in Amazonian Perù

SDSS-IV MaNGA: Spatially resolved star formation histories in galaxies as a function of galaxy mass and type

© 2016 The Authors. We study the internal gradients of stellar population propertieswithin 1.5 Re for a representative sample of 721 galaxies, with stellar masses ranging between 109M⊙ and 1011.5M⊙ from the SDSS-IV MaNGA Integral-Field-Unit survey. Through the use of our full spectral fitting code FIREFLY, we derive light- and mass-weighted stellar population properties and their radial gradients, as well as full star formation and metal enrichment histories. We also quantify the impact that different stellar population models and full spectral fitting routines have on the derived stellar population properties and the radial gradient measurements. In our analysis, we find that age gradients tend to be shallow for both early-type and late-type galaxies. Mass-weighted age gradients of early-types arepositive (~0.09 dex/Re) pointing to 'outside- in' progression of star formation, while late-type galaxies have negative light-weighted age gradients (~-0.11 dex/Re), suggesting an 'inside-out' formation of discs. We detect negative metallicity gradients in both early- and late-type galaxies, but these are significantly steeper in late-types, suggesting that the radial dependence of chemical enrichment processes and the effect of gas inflow and metal transport are far more pronounced in discs. Metallicity gradients of both morphological classes correlate with galaxy mass, with negative metallicity gradients becoming steeper with increasing galaxy mass. The correlation with mass is stronger for late-type galaxies, with a slope of d(∇[Z/H])/d(logM) ~ -0.2 ± 0.05, compared to d(∇[Z/H])/d(logM) ~ -0.05 ± 0.05 for early-types. This result suggests that the merger history plays a relatively small role in shaping metallicity gradients of galaxies